# Sustainable Cold Mix Asphalt Repair: An Analytic Hierarchy Process–Grey Relational Analysis Optimization Framework

## TL;DR

This study introduces a new optimization framework to improve cold mix asphalt pothole repairs, enhancing quality and reducing environmental impact.

## Contribution

A novel integration of AHP and GRA to optimize CMA repair processes under operational constraints.

## Key findings

- Material placement and compaction are the most critical phases for repair quality.
- Optimized protocols outperformed current municipal practices in alignment with ideal benchmarks.
- The framework reduces reworks, lowering material use and environmental burden.

## Abstract

Cold mix asphalt (CMA) pothole repair is extensively utilized in time-sensitive highway maintenance due to its rapid deployment and all-weather applicability. However, premature failures caused by suboptimal construction practices under operational constraints (e.g., emergency repairs and adverse weather) necessitate frequent reworks, inadvertently escalating material consumption and associated environmental burdens. To address this challenge, this study proposes a quality-driven optimization framework integrating enhanced Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA). The methodology systematically evaluates 18 technical parameters across six critical construction phases—grooving/molding, cleaning/drying, bonding layer application, material paving, compaction, and edge trimming—to identify dominant quality determinants. The analysis highlights material placement and compaction as the most significant phases in the repair process, with specific technical parameters such as compaction standardization, paving uniformity, compactor dimension selection, and material application emerging as key quality drivers. To assess the feasibility of the optimized process, a grey relational analysis was adopted to compare the proposed protocol with the cold-patch practices currently adopted by two municipal maintenance agencies in Shanghai, demonstrating superior alignment with an ideal repair benchmark. The developed model empowers highway agencies to achieve dual operational–environmental gains: maintaining urgent repair efficiency while mitigating secondary resource depletion through reduced repetitive interventions.